CCBR XXXX: Your project Title

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Author
Affiliations

Samarth Mathur

CCR Collaborative Bioinformatics Resource, Office of Science and Technology Resources, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA

Advanced Biomedical Computational Science, Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USA

Published

August 7, 2025

📝 Last modified: 08-07-2025

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Data Visualization Examples

Code 
# Generate random data
set.seed(123)
x <- runif(10, 0, 10)
y <- runif(10, 0, 10)

# Create scatter plot
plot(x, y, 
     pch = 16, 
     col = "#4e9db5", 
     cex = 1.5,
     main = "Random Scatter Plot",
     xlab = "X values", 
     ylab = "Y values")

Code 
# Sample data
categories <- c("A", "B", "C", "D", "E")
values <- c(23, 17, 35, 29, 12)

# Create bar plot
barplot(values, 
        names.arg = categories,
        col = "#7cc349",
        main = "Category Comparison",
        xlab = "Categories", 
        ylab = "Values",
        border = "#528230")

Code 
# Data for pie chart
labels <- c("Research", "Analysis", "Writing", "Review")
sizes <- c(35, 25, 25, 15)
colors <- c("#4e9db5", "#7cc349", "#ecba4c", "#296b7f")

# Create pie chart
pie(sizes, 
    labels = labels, 
    col = colors,
    main = "Project Time Distribution")

Different Base R Styles

Code 
# Random data with grid
set.seed(789)
x <- runif(10, 1, 8)
y <- runif(10, 2, 9)

# Enhanced scatter plot
plot(x, y, 
     pch = 19, 
     col = "#296b7f", 
     cex = 2,
     main = "Enhanced Scatter Plot",
     xlab = "X values", 
     ylab = "Y values",
     xlim = c(0, 10),
     ylim = c(0, 10))
grid(col = "gray", lty = "dotted")

Code 
# Data for horizontal bars
items <- c("Item A", "Item B", "Item C", "Item D")
counts <- c(15, 28, 22, 19)

# Horizontal barplot
barplot(counts, 
        names.arg = items,
        horiz = TRUE,
        col = "#7cc349",
        main = "Horizontal Bar Chart",
        xlab = "Count",
        border = "#528230")

Code 
# Simple data
activity <- c("Coding", "Testing", "Documentation", "Meetings")
time <- c(40, 20, 25, 15)
colors <- c("#4e9db5", "#7cc349", "#ecba4c", "#19424e")

# Create pie chart
pie(time, 
    labels = paste(activity, "(", time, "%)", sep = ""), 
    col = colors,
    main = "Time Allocation",
    clockwise = TRUE)

More Base R Variations

Code 
# Time series style data
set.seed(999)
time <- 1:10
values <- cumsum(rnorm(10, 0.5, 1))

# Line plot with points
plot(time, values, 
     type = "b",
     pch = 16,
     col = "#296b7f",
     lwd = 2,
     main = "Trend Over Time",
     xlab = "Time Point",
     ylab = "Cumulative Value")

Code 
# Matrix for stacked bars
data_matrix <- matrix(c(12, 8, 15, 
                       18, 12, 10, 
                       10, 15, 20), 
                     nrow = 3, byrow = TRUE)
colnames(data_matrix) <- c("Group A", "Group B", "Group C")
rownames(data_matrix) <- c("Category 1", "Category 2", "Category 3")

# Stacked barplot
barplot(data_matrix, 
        col = c("#4e9db5", "#7cc349", "#ecba4c"),
        main = "Stacked Bar Chart",
        xlab = "Groups",
        ylab = "Values",
        legend.text = TRUE)

Code 
# Split plotting area for multiple pies
par(mfrow = c(1, 2))

# First pie
pie1 <- c(30, 70)
pie(pie1, 
    labels = c("Yes", "No"), 
    col = c("#7cc349", "#ecba4c"),
    main = "Survey A")

# Second pie  
pie2 <- c(45, 55)
pie(pie2, 
    labels = c("Pass", "Fail"), 
    col = c("#4e9db5", "#296b7f"),
    main = "Survey B")

Code 
# Reset to single plot
par(mfrow = c(1, 1))

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Created by Samarth Mathur, PhD

My Github CCBR Team